Biomass has great potential to meet greenhouse gas reduction and fuel supply security in the future. Although the grate biomass combustors are increasingly deployed worldwide to generate energy from solid biomass, challenges in understanding the system operation to some extent have remained. This paper analyzes the effects of fuel composition uncertainty on the biomass grate combustor’s performance, which have not been solved so far. A 1D transient numerical model of the biomass fuel bed combustion is developed. A set of thermal gravimetric analysis (TGA) experiments on randomly selected biomass particles from the same fuel supplier are conducted to achieve the proximate analysis of the particles. The Bayesian model averaging (BMA) method was exercised to deliver the fuel uncertainty into the CFD model of the fuel bed. Results revealed that the fuel composition variability can significantly affect the solid fuel conversion so that ignoring them can result in incomplete combustion. In three various scenarios proposed, combustor is analyzed: (I) using primary fuel composition given by the producer, (II) mean value of fuel composition obtained from the BMA model, and lastly (III) fuel composition under fully uncertainty conditions. Results revealed that overlooking the fuel uncertainty results in overestimating system energy output by 8.3% and also can waste 1611-kg feed annually which is roughly 5% of whole consumed fuel. Meanwhile, owing to uncertainty associated with fuel composition, flame temperature can fluctuate up to 15 °C. According to the uncertainty analysis, char content of wood pellets has dominating role in fuel quality. Finally, a life cycle analysis (LCA) is conducted for the first, second, and coal-fueled system scenarios.

生物质在未来减少温室气体排放和燃料供应安全方面具有巨大潜力。尽管炉排生物质燃烧器在世界范围内越来越多地用于从固体生物质中产生能量，但是在某种程度上理解系统的运行仍然存在挑战。本文分析了燃料成分不确定性对生物质炉排燃烧器性能的影响，目前尚未解决。建立了生物质燃料床燃烧的一维瞬态数值模型。对来自同一燃料供应商的随机选择的生物质颗粒进行了一组热重分析（TGA）实验，以实现对颗粒的近距离分析。运用贝叶斯模型平均（BMA）方法将燃料不确定性传递到燃料床的CFD模型中。结果表明，燃料成分的变化会显着影响固体燃料的转化率，因此忽略它们可能导致不完全燃烧。在提出的三种不同方案中，对燃烧室进行了分析：（I）使用生产者提供的一次燃料成分，（II）从BMA模型获得的燃料成分平均值，最后（III）在完全不确定性条件下的燃料成分。结果表明，忽略燃料不确定性会导致系统能量输出高估8.3％，并且每年可能浪费1611千克饲料，大约占总消耗燃料的5％。同时，由于与燃料成分有关的不确定性，火焰温度可能会波动至15°C。根据不确定性分析，木屑颗粒的炭含量在燃料质量中起主要作用。最后，